Predicting skin sensitisation using a decision tree integrated testing strategy with an in silico model and in chemico/in vitro assays.
Regul Toxicol Pharmacol
; 76: 30-8, 2016 Apr.
Article
in En
| MEDLINE
| ID: mdl-26796566
ABSTRACT
There is a pressing need for non-animal methods to predict skin sensitisation potential and a number of in chemico and in vitro assays have been designed with this in mind. However, some compounds can fall outside the applicability domain of these in chemico/in vitro assays and may not be predicted accurately. Rule-based in silico models such as Derek Nexus are expert-derived from animal and/or human data and the mechanism-based alert domain can take a number of factors into account (e.g. abiotic/biotic activation). Therefore, Derek Nexus may be able to predict for compounds outside the applicability domain of in chemico/in vitro assays. To this end, an integrated testing strategy (ITS) decision tree using Derek Nexus and a maximum of two assays (from DPRA, KeratinoSens, LuSens, h-CLAT and U-SENS) was developed. Generally, the decision tree improved upon other ITS evaluated in this study with positive and negative predictivity calculated as 86% and 81%, respectively. Our results demonstrate that an ITS using an in silico model such as Derek Nexus with a maximum of two in chemico/in vitro assays can predict the sensitising potential of a number of chemicals, including those outside the applicability domain of existing non-animal assays.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Skin
/
Computer Simulation
/
Decision Trees
/
Dermatitis, Irritant
/
Dermatitis, Allergic Contact
/
Skin Irritancy Tests
/
Irritants
/
Animal Testing Alternatives
Type of study:
Health_economic_evaluation
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Animals
/
Humans
Language:
En
Journal:
Regul Toxicol Pharmacol
Year:
2016
Document type:
Article